Create an SDF library from a SMILES CSV with Python

Steps

1. Create molecules.csv with name and smiles columns, then keep a source copy.
2. Parse each row locally, attach source_row and source_smiles SD properties, and write only valid structures to the SDF.
3. Write molecule-report.csv for every source row before filtering or interpreting output.

import csv
import chematic

report = []
with open("molecules.csv", newline="", encoding="utf-8") as src, \
+     chematic.SDWriter("molecules.sdf") as sdf:
    for source_row, row in enumerate(csv.DictReader(src), start=2):
        smiles = row.get("smiles", "").strip()
        name = row.get("name", "").strip() or f"row_{source_row}"
        try:
            mol = chematic.from_smiles(smiles)
            mol.SetProp("_Name", name)
            mol.SetProp("source_row", str(source_row))
            mol.SetProp("source_smiles", smiles)
            sdf.write(mol)
            report.append({"source_row": source_row, "name": name, "smiles": smiles, "status": "written", "error": ""})
        except ValueError as error:
            report.append({"source_row": source_row, "name": name, "smiles": smiles, "status": "invalid_smiles", "error": str(error)})

with open("molecule-report.csv", "w", newline="", encoding="utf-8") as out:
    writer = csv.DictWriter(out, fieldnames=["source_row", "name", "smiles", "status", "error"])
    writer.writeheader()
    writer.writerows(report)

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